A comparison of transcriptional profiles derived from different tissues in a given species or among different species assumes that commonalities reflect evolutionarily conserved programs and that differences reflect species or tissue responses to environmental conditions or developmental program staging. Apparently conflicting results have been published regarding whether organ-specific transcriptional patterns dominate over species-specific patterns, or vice versa, making it unclear to what extent the biology of a given organism can be extrapolated to another. These studies have in common that they treat the transcriptomes monolithically, implicitly ignoring that each gene is likely to have a specific pattern of transcriptional variation across organs and species.
Researchers at the Centre for Genomic Regulation (CRG) used linear models to quantify this pattern. They found a continuum in the spectrum of expression variation: the expression of some genes varies considerably across species and little across organs, and simply reflects evolutionary distance. At the other extreme are genes whose expression varies considerably across organs and little across species; these genes are much more likely to be associated with diseases than are genes whose expression varies predominantly across species.
Proportion of expression variance explained after centering and scaling each gene expression across species (x-axis) or across organs (y-axis) for the 6283 orthologous genes. When centering and scaling across species, the variance explained by species is 0 and there is only variance explained by organ (x-axis). Conversely, the y-axis is the proportion of variance explained by species after the variance across organs becomes 0 because of centering and scaling across organs. Dots are colored based on the class assigned to each gene. A PCA is performed on the gene expression of all 6283 orthologous genes after centering and scaling their expression across organs.
Whether transcriptomes, when considered globally, cluster preferentially according to one component or the other may not be a property of the transcriptomes, but rather a consequence of the dominant behavior of a subset of genes. Therefore, the values of the components of the variance of expression for each gene could become a useful resource when planning, interpreting, and extrapolating experimental data from mouse to humans.